import pandas as pd

​

#find dataset 

data = pd.read_csv(r"C:\Users\cbenj\OneDrive\Desktop\School\AdvanceData\Data Comparison\owid-covid-data.csv")

​

# Filter data for the years 2020 to 2023

data = data[(data['date'] >= '2020-01-01') & (data['date'] <= '2023-12-31')]

​

# Group the data by "location" (country) and "date"

grouped_data = data.groupby(['location', 'date'])

​

# Calculate the sum of "total deaths," "total vaccinations," and "total cases" for each country and date

summary_data = grouped_data[['total_deaths', 'total_vaccinations', 'total_cases', 'population']].sum().reset_index()

​

# Save the summary data to a new CSV file

summary_data.to_csv('summary_data.csv', index=False)

​

data['date'] = pd.to_datetime(data['date'])

​

import matplotlib.pyplot as plt

from matplotlib.ticker import MaxNLocator

continent = data['location'].unique()

​

plt.figure(figsize=(12,6))

for location in continent:

    country_data = data[data['location'] == location]

    plt.plot(country_data['date'], country_data['total_deaths'], label=location)

​

plt.xlabel('Date')

plt.ylabel('Total Deaths')

plt.title('Time series of total deaths')

plt.legend(loc='upper left', bbox_to_anchor=(1,1))

plt.show()

​

plt.figure(figsize=(12, 6))

for location in continent:

    country_data = data[data['location'] == location]

    plt.plot(country_data['date'], country_data['total_vaccinations'], label=location)

​

plt.xlabel('Date')

plt.ylabel('Total Vaccinated')

plt.title('Time series of total vaccinated')

plt.legend(loc='upper left', bbox_to_anchor=(1, 1))

plt.show()

​

import plotly.graph_objs as go

import plotly.subplots as sp

from plotly.subplots import make_subplots

import ipywidgets as widgets

from IPython.display import display

from IPython.display import clear_output

​

​

# Create a function to update the chart based on the selected data

def update_chart(selected_location, selected_data):

    data_subset = data[data['location'] == selected_location]

    data_column = 'total_deaths' if selected_data == 'total_deaths' else 'total_vaccinations'

​

    fig = make_subplots(rows=1, cols=1)

    trace = go.Scatter(x=data_subset['date'], y=data_subset[data_column], mode='lines', name=selected_data)

​

    fig.add_trace(trace)

    fig.update_xaxes(title='Date')

    fig.update_yaxes(title=selected_data)

    fig.update_layout(title=f'{selected_data} Over Time')

​

    return fig

​

# Dropdown widget for selecting location

location_dropdown = widgets.Dropdown(options=data['location'].unique(), description='Location:')

​

# Radio buttons widget for selecting data type

data_radio = widgets.RadioButtons(options=['total_deaths', 'total_vaccinations'], description='Data Type:')

​

# Function to update the chart when widgets change

def on_change(change):

    if change['name'] == 'value':

        clear_output()

        display(location_dropdown, data_radio)

        display(update_chart(location_dropdown.value, data_radio.value))

​

location_dropdown.observe(on_change)

data_radio.observe(on_change)

​

# Initial display

display(location_dropdown, data_radio)

display(update_chart(location_dropdown.value, data_radio.value))

​

# Create subplots

fig = sp.make_subplots(rows=1, cols=2, shared_xaxes=True)

​

# Add the total_deaths trace

trace_deaths = go.Scatter(x=data['date'], y=data['total_deaths'], name='Total Deaths')

fig.add_trace(trace_deaths, row=1, col=1)

​

# Add the total_vaccinated trace (corrected column name)

trace_vaccinated = go.Scatter(x=data['date'], y=data['total_vaccinations'], name='Total Vaccinated')

fig.add_trace(trace_vaccinated, row=1, col=2)

​

# Update layout for the subplots

fig.layout.update(

    title='Total Deaths and Total Vaccinated Over Time',

    xaxis=dict(title='Date'),

    yaxis=dict(title='Counts')

)

​

# Create updatemenu

updatemenus = [

    dict(

        buttons=list([

            dict(label='Total Deaths',

                 method='relayout',

                 args=['xaxis.title.text', 'Date'],

                 args2=[{'xaxis.title.text': 'Total Deaths'}]),

            dict(label='Total Vaccinated',

                 method='relayout',

                 args=['xaxis.title.text', 'Date'],

                 args2=[{'xaxis.title.text': 'Total Vaccinated'}])

        ]),

        direction='down',

        showactive=True

    )

]

​

# Add updatemenu to the layout

fig.layout.updatemenus = updatemenus

​

fig.show()